code: def __init__(
      self,
      hidden_size: int,
      intermediate_size: int,
      activation: Union[str, torch.nn.Module],
      pool: bool = False,
  ):
      super().__init__()
      self.dense = torch.nn.Linear(hidden_size, intermediate_size)
      if isinstance(activation, str):
          self.act_fn = ACT2FN[activation]
      else:
          self.act_fn = activation
      self.pool = pool
  
file_path: allennlp/allennlp/modules/transformer/activation_layer.py
imports: from typing import Union
  import torch
  from allennlp.common import FromParams
  from allennlp.modules.transformer.transformer_module import TransformerModule
  from transformers.models.bert.modeling_bert import ACT2FN
label_desc: Use image node_id 1 to create a new ActivationLayer object from inherited base classes: TransformerModule, FromParams with example: obj = ActivationLayer(hidden_size, intermediate_size, activation, pool)